86192017-09-16Research of Off-Nominal Airport Traffic Management using a Surface Management System-Based Simulation, Phase ICompletedJan 2010Jul 2010The proposed project is complimentary and directly beneficial to NASA's Safe and Efficient Surface Operations (SESO) research. NASA has previously developed a modular architecture for testing airport control concepts and algorithms within the Surface Management System (SMS). However, SMS currently uses live or pre-recorded surveillance data and, therefore, must be connected to a separate simulation environment. We will develop a self-contained, fast-time SMS simulation environment by incorporating an aircraft taxi model. The proposed stand-alone platform would complement NASA's current SMS-ATG environment by providing a fast-time simulation capability that uses the desired SMS plug-in architecture. We will also develop and integrate within the SMS simulation departure scheduling and taxi planning algorithms. These algorithms will supplement NASA's existing work and be independent of external optimization solvers. Lastly, the project will apply the fast-time simulation and integrated planning algorithms to study JFK airport surface traffic management under regular and off-nominal conditions, studies that complement NASA's research. JFK was chosen because of its complex geometry and traffic. We have received permission from the FAA to use JFK data, which is already available to Mosaic ATM as part of our FAA work.Potential NASA Commercial Applications: The SMS simulation capability developed within this project will be useful for FAA research and we have identified opportunities to apply this capability within FAA projects on which we are working. The FAA will also benefit from the surface traffic management algorithms tested throughout this project. As described in the FAA's letter of support, this work contributes to future FAA technology segments identified by the RTT for technology transfer from NASA to the FAA. Universities and other research organizations could also build on this work. Lastly, elements of the developed algorithms may be useful to develop automation to help flight operators participate effectively in future collaborative airport traffic management.233SBIR/STTRSpace Technology Mission DirectorateAmes Research CenterARCNASA CenterMoffett FieldCAMosaic ATM, Inc.IndustryLeesburgVACaliforniaVirginiaTherese GriebelCarlos TorrezSteve Atkins